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The interplay of artificial intelligence, machine learning, and data analytics in digital marketing and promotions: a review and research agenda

Author

Listed:
  • Rituparna Basu

    (International Management Institute Kolkata)

  • Md. Nayeem Aktar

    (International Management Institute Kolkata)

  • Satish Kumar

    (Indian Institute of Management Nagpur)

Abstract

In contemporary data-driven business environments, the adoption of artificial intelligence (AI), machine learning (ML), and data analytics has enabled the practice of digital marketing and promotions with incomparable efficiency. To provide insights into the current trends and future directions of research in this overlapping knowledge cluster, the present study examines 94 published journal articles to date obtained from the Scopus database. Utilizing the systematic performance analysis and review method (SPAR-4-SLR), the paper uses Excel and VOSviewer to present a bibliometric review. Following a thorough disciplinary analysis of the articles, the paper identifies five main research clusters representing the domain (i) AI and Digital Marketing (ii) Branding Automation and Engagement (iii) Optimizing E-Commerce and Social Media Marketing (iv) AI-Powered Personalized Marketing (v) Emerging Tools in Digital Marketing. In this paper, we draw on some of the key theories relevant to the field and develop an Antecedent-Decision-Outcome framework that examines the factors affecting the use of digital technologies and the benefits derived from them. Pivotal research questions are also articulated in this study to guide future inquiries in this evolving area of study.

Suggested Citation

  • Rituparna Basu & Md. Nayeem Aktar & Satish Kumar, 2025. "The interplay of artificial intelligence, machine learning, and data analytics in digital marketing and promotions: a review and research agenda," Journal of Marketing Analytics, Palgrave Macmillan, vol. 13(2), pages 267-287, June.
    • Handle: RePEc:pal:jmarka:v:13:y:2025:i:2:d:10.1057_s41270-024-00355-6
    DOI: 10.1057/s41270-024-00355-6
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